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Removed logic of building example_input by shape. (#20859)

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Anastasiia Pnevskaia 2023-11-03 17:45:34 +01:00 committed by GitHub
parent 86c638a595
commit cc389c23ca
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GPG Key ID: 4AEE18F83AFDEB23
3 changed files with 36 additions and 46 deletions
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31
src/bindings/python/src/openvino/frontend/tensorflow/utils.py
View File

@ -118,33 +118,6 @@ def get_input_spec_from_model(model):
return input_spec
def create_example_input_by_user_shapes(input_shapes, input_types):
import tensorflow as tf
if input_shapes is None:
return None
if isinstance(input_shapes, dict):
res = {}
for name, shape in input_shapes.items():
shape = get_static_shape(shape, 1)
args = {}
if name in input_types:
args["dtype"] = input_types[name]
tensor = tf.zeros(shape=shape, **args)
res[name] = tensor
return res
elif isinstance(input_shapes, list):
res = []
for idx, shape in enumerate(input_shapes):
shape = get_static_shape(shape, 1)
args = {}
if idx < len(input_types):
args["dtype"] = input_types[idx]
tensor = tf.zeros(shape=shape, **args)
res.append(tensor)
return res
raise Exception("Could not create example input by provided shape {}".format(input_shapes))
def get_concrete_func(tf_function, example_input, input_needs_packing, error_message, use_example_input=True):
"""
Runs tracing of TF function and returns a concrete function.
@ -281,10 +254,6 @@ def trace_tf_model(model, input_shapes, input_types, example_input):
if example_input is not None:
concrete_func = get_concrete_func(tf_function, example_input, input_needs_packing,
"Could not trace the TF model with the following error: {}")
elif are_shapes_defined(input_shapes):
inp = create_example_input_by_user_shapes(input_shapes, input_types)
concrete_func = get_concrete_func(tf_function, inp, input_needs_packing,
"Could not trace the TF model with the following error: {}")
else:
if isinstance(tf_function, tf.types.experimental.GenericFunction) and \
tf_function.input_signature is not None:

28
tests/layer_tests/mo_python_api_tests/test_mo_convert_tf.py
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@ -139,7 +139,8 @@ def create_tf_module(tmp_dir):
model_ref = Model([sigm], parameter_list, "test")
net = Net()
return net, model_ref, {'input': [PartialShape([1, 2, 3]), PartialShape([1, 2, 3])]}
return net, model_ref, {'example_input': (np.random.rand(1, 2, 3).astype(np.float32),
np.random.rand(1, 2, 3).astype(np.float32))}
def create_tf_module_layout_list(tmp_dir):
@ -166,7 +167,8 @@ def create_tf_module_layout_list(tmp_dir):
model_ref.inputs[1].node.layout = Layout('NHC')
net = Net()
return net, model_ref, {'input_shape': [PartialShape([1, 2, 3]), PartialShape([1, 2, 3])], 'layout': ["NCH", "NHC"],
return net, model_ref, {'example_input': (np.random.rand(1, 2, 3).astype(np.float32),
np.random.rand(1, 2, 3).astype(np.float32)), 'layout': ["NCH", "NHC"],
'use_convert_model_from_mo': True}
@ -193,7 +195,10 @@ def create_tf_module_dynamic(tmp_dir):
model_ref = Model([sigm], parameter_list, "test")
net = Net()
return net, model_ref, {'input': input_shapes}
return net, model_ref, {'input': input_shapes,
'example_input': (np.random.rand(1, 2, 3).astype(np.float32),
np.random.rand(1, 2, 3).astype(np.float32))
}
def create_keras_layer(tmp_dir):
@ -217,7 +222,9 @@ def create_keras_layer(tmp_dir):
model_ref = Model([sigm], parameter_list, "test")
net = LayerModel()
return net, model_ref, {'input': [PartialShape([1, 2, 3]), PartialShape([1, 2, 3])]}
return net, model_ref, {'example_input': (np.random.rand(1, 2, 3).astype(np.float32),
np.random.rand(1, 2, 3).astype(np.float32))
}
def create_keras_layer_dynamic(tmp_dir):
@ -243,7 +250,10 @@ def create_keras_layer_dynamic(tmp_dir):
model_ref = Model([sigm], parameter_list, "test")
net = LayerModel()
return net, model_ref, {'input': input_shapes}
return net, model_ref, {'input': input_shapes,
'example_input': (np.random.rand(1, 2, 3).astype(np.float32),
np.random.rand(1, 2, 3).astype(np.float32))
}
def create_tf_checkpoint(tmp_dir):
@ -531,17 +541,19 @@ def create_keras_layer_with_example_input_2(tmp_dir):
def create_keras_layer_with_input_shapes_case1(tmp_dir):
model, model_ref = create_keras_layer_input_list()
return model, model_ref, {'input': [[1, 2, 3], [1, 2, 3]]}
return model, model_ref, {'example_input': (np.random.rand(1, 2, 3).astype(np.float32),
np.random.rand(1, 2, 3).astype(np.float32))}
def create_keras_layer_with_input_shapes_case2(tmp_dir):
model, model_ref = create_keras_layer_input_list()
return model, model_ref, {'input': [([1, 2, 3], np.float32), ([1, 2, 3], np.float32)]}
return model, model_ref, {'example_input': (np.random.rand(1, 2, 3).astype(np.float32),
np.random.rand(1, 2, 3).astype(np.float32))}
def create_keras_layer_with_input_shapes_case3(tmp_dir):
model, model_ref = create_keras_layer_input_dict_one_inp()
return model, model_ref, {'input': [('args', [1, 2, 3])]}
return model, model_ref, {'example_input': {"args": np.random.rand(1, 2, 3).astype(np.float32)}}
def create_keras_layer_with_input_shapes_case4(tmp_dir):

23
tests/layer_tests/ovc_python_api_tests/test_tf.py
View File

@ -131,7 +131,8 @@ def create_tf_module(tmp_dir):
model_ref = Model([sigm], parameter_list, "test")
net = Net()
return net, model_ref, {'input': [PartialShape([1, 2, 3]), PartialShape([1, 2, 3])]}
return net, model_ref, {'example_input': (np.random.rand(1, 2, 3).astype(np.float32),
np.random.rand(1, 2, 3).astype(np.float32))}
def create_tf_module_dynamic(tmp_dir):
@ -155,7 +156,9 @@ def create_tf_module_dynamic(tmp_dir):
model_ref = Model([sigm], parameter_list, "test")
net = Net()
return net, model_ref, {'input': input_shapes}
return net, model_ref, {'input': input_shapes,
'example_input': (np.random.rand(1, 2, 3).astype(np.float32),
np.random.rand(1, 2, 3).astype(np.float32))}
def create_keras_layer(tmp_dir):
@ -178,7 +181,8 @@ def create_keras_layer(tmp_dir):
model_ref = Model([sigm], parameter_list, "test")
net = LayerModel()
return net, model_ref, {'input': [PartialShape([1, 2, 3]), PartialShape([1, 2, 3])]}
return net, model_ref, {'example_input': (np.random.rand(1, 2, 3).astype(np.float32),
np.random.rand(1, 2, 3).astype(np.float32))}
def create_keras_layer_dynamic(tmp_dir):
@ -203,7 +207,10 @@ def create_keras_layer_dynamic(tmp_dir):
model_ref = Model([sigm], parameter_list, "test")
net = LayerModel()
return net, model_ref, {'input': input_shapes}
return net, model_ref, {'input': input_shapes,
'example_input': (np.random.rand(1, 2, 3).astype(np.float32),
np.random.rand(1, 2, 3).astype(np.float32))
}
def create_tf_checkpoint(tmp_dir):
@ -478,17 +485,19 @@ def create_keras_layer_with_example_input_2(tmp_dir):
def create_keras_layer_with_input_shapes_case1(tmp_dir):
model, model_ref = create_keras_layer_input_list()
return model, model_ref, {'input': [[1, 2, 3], [1, 2, 3]]}
return model, model_ref, {'example_input': (np.random.rand(1, 2, 3).astype(np.float32),
np.random.rand(1, 2, 3).astype(np.float32))}
def create_keras_layer_with_input_shapes_case2(tmp_dir):
model, model_ref = create_keras_layer_input_list()
return model, model_ref, {'input': [([1, 2, 3], np.float32), ([1, 2, 3], np.float32)]}
return model, model_ref, {'example_input': (np.random.rand(1, 2, 3).astype(np.float32),
np.random.rand(1, 2, 3).astype(np.float32))}
def create_keras_layer_with_input_shapes_case3(tmp_dir):
model, model_ref = create_keras_layer_input_dict_one_inp()
return model, model_ref, {'input': [('args', [1, 2, 3])]}
return model, model_ref, {'example_input': {'args': np.random.rand(1, 2, 3).astype(np.float32)}}
def create_keras_layer_with_input_shapes_case4(tmp_dir):